{"id":"W2514380113","doi":"10.2139/ssrn.2834019","title":"Welfare Implications of Congestion Pricing: Evidence from SFpark","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Economics; Welfare; Business; Financial economics; Market economy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009720667,0.00009996089,0.0001639403,0.00008781797,0.0003683717,0.0001018183,0.0006069265,0.00006870434,0.00003659554],"category_scores_gemma":[0.0003487862,0.00009639403,0.00006312519,0.00006339688,0.00004913924,0.0003016615,0.00004099135,0.0009560756,0.00003691564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006328525,"about_ca_system_score_gemma":0.0003546077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003719676,"about_ca_topic_score_gemma":0.0007837075,"domain_scores_codex":[0.9983743,0.00004598399,0.0002615097,0.0001220117,0.0002369485,0.0009592047],"domain_scores_gemma":[0.9990453,0.00008879165,0.0001494556,0.0005216523,0.0001284862,0.00006633774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001071639,0.00009670058,0.5465397,0.0001857557,0.001362501,0.00001102936,0.001043389,0.009616397,0.1777368,0.08762792,0.002142525,0.1735301],"study_design_scores_gemma":[0.0007423204,0.000202303,0.9460232,0.0005850794,0.00007403934,0.0002897858,0.0005199737,0.003682191,0.006485566,0.03624685,0.004756322,0.0003923858],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9763606,0.004823416,0.01428652,0.001656769,0.0003722802,0.0001708957,0.000006613463,0.00007498208,0.002247997],"genre_scores_gemma":[0.9979161,0.0014355,0.00009182542,0.000001814311,0.000259185,0.0000102904,0.000001819932,0.00002414749,0.0002593061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3994835,"threshold_uncertainty_score":0.4153726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03019802337017125,"score_gpt":0.3004641498754623,"score_spread":0.270266126505291,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}